Operation of vessels in a maritime setting involves adherence to standardized navigation rules that are intended to avoid collisions or other dangerous navigation conditions. These standardized navigation rules (the International Regulations for Preventing Collisions at Sea, known as COLREGS) are well known and are generally adhered to by all vessels, from small sailing vessels to commercial vessels such as cruise liners and shipping vessels such as container ships and tankers, as well as military vessels when operating under conventional operating conditions.
In recent years, significant technological advancements have increased on-board capabilities of Unmanned Surface Vehicles (USVs), so that their intended mission scenarios now routinely include environments shared with other seagoing traffic. See Program Executive Officer for Littoral and Mine Warfare (PEO (LMW)), “The Navy Unmanned Surface Vehicle (USV) Master Plan,” U.S. Navy, Tech. Rep., 2007; and J. Larson, M. Bruch, and J. Ebken, “Autonomous navigation and obstacle avoidance for unmanned surface vehicles,” in SPIE Proc. 6230: Unmanned Systems Technology VIII, 2006, pp. 17-20.
In maritime navigation, ships should obey the International Regulations for Preventing Collisions at Sea (known as COLREGS, for Collision Regulations), agreed to by the International Maritime Organization (IMO) in 1972. See U.S. Department Of Homeland Security, U.S. Coast Guard, Navigation Rules. Paradise Cay Publications, 2010. These “rules of the road” specify the types of maneuvers that should be taken in situations where there is a risk of collision. When USVs are operated in the vicinity of other vessels, their navigation algorithms must abide by COLREGS, so that the USVs can safely avoid other vessels and the drivers of other vessels can rely on a range of safe behaviors from the USVs. A variety of approaches to maritime navigation obeying COLREGS has been proposed in the past, such as fuzzy logic (see S.-M. Lee, K.-Y. Kwon, and J. Joh, “A Fuzzy Logic for Autonomous Navigation of Marine Vehicles Satisfying COLREG Guidelines,” International Journal of Control, Automation, and Systems, vol. 2, no. 2, pp. 171-181, 2004; and L. P. Perera, J. P. Carvalho, and C. G. Soares, “Autonomous guidance and navigation based on the COLREGs rules and regulations of collision avoidance,” in Proceedings of the International Workshop “Advanced Ship Design for Pollution Prevention”, 2009, pp. 205-216.), evolutionary algorithms (see J. Colito, “Autonomous Mission Planning and Execution for Unmanned Surface Vehicles in Compliance with the Marine Rules of the Road,” Master's thesis, University of Washington, 2007.), neural networks, hybrids of these algorithms (see T. Statheros, G. Howells, and K. M. Maier, “Autonomous Ship Collision Avoidance Navigation Concepts, Technologies and Techniques,” Journal of Navigation, vol. 61, no. 1, pp. 129-142, 2008.), interval programming (see M. Benjamin, J. Curcio, and P. Newman, “Navigation of Unmanned Marine Vehicles in Accordance with the Rules of the Road,” in Proceedings of the IEEE International Conference on Robotics and Automation, 2006.), and 2D grid maps (see K. Teo, K. W. Ong, and H. C. Lai, “Obstacle Detection, Avoidance and Anti Collision for MEREDITH AUV,” in OCEANS, MTS/IEEE Biloxi—Marine Technology for Our Future: Global and Local Challenges, 2009.). However, these previous approaches do not scale well to multiple traffic boats and multiple COLREGS rules, especially on robotic platforms with real-time computational requirements. Furthermore, most results cited in the literature are limited to simulation, where real world issues such as uncertainties of USV motion, computational and communication delays, and noise in the perception system are not present.
There is a need for systems and methods for navigating and operating autonomous waterborne vessels that provide safe operation while accomplishing a desired sailing action.